1 |
Kim, M.I., Lee, W.K., and Kwon, T.H. (2011), Early detecting damaged trees by pine wilt disease using DI(Detection Index) from portable near infrared camera, Journal of Korean Society of Forest Science, Vol. 100, No.3 , pp. 374~381. (in Korean with English abstract). https://doi.org/10.14578/jkfs.2011.100.3.8
DOI
|
2 |
Korea Forest Service. (2016), National Forest Inventory Report, Korea Forest Service, Daejeon, Korea, pp. 1-192 (in Korean).
|
3 |
Lee, K.W. and Park, J.K. (2019), Economic evaluation of unmanned aerial vehicle for forest pest monitoring, Journal of the Korea Academia Industrial cooperation Society, Vol. 20, No. 1, pp. 440-446 (in Korean with English abstract). https://doi.org/10.5762/KAIS.2019.20.1.440
DOI
|
4 |
Lee, N.K., Kim, J.Y., and Shim, J.H. (2021), Empirical study on analyzing training data for CNN-based product classification deep learning model, The Journal of Society for e-Business Studies, Vol. 26, No. 1, pp. 107-126. (in Korean with English abstract) https://doi.org/10.7838/jsebs.2021.26.1.107
DOI
|
5 |
Lim, E.T. and Do, M.S. (2021), Pine wilt disease detection based on deep learning using an unmanned aerial vehicle. Journal of Civil and Environmental Engineering Research, Vol. 41, No. 3, pp. 317-325. (in Korean with English abstract). https://doi.org/10.12652/Ksce.2021.41.3.0317
DOI
|
6 |
Lee, S.K. and Seo, S.T. (2016), First report of Armillaria root disease caused by Armillaria tabescens on carpinus tschonoskii in south Korea. Plant Disease. Vol. 100, No. 1, pp. 213.
|
7 |
Kim, S.H, (2022), A Study on the Improvement of Orthoimage Detection by the U-Net model : Focusing on the Case of Pine Wilt Disease, Ph.D. dissertation, Youngnam University, Gyeongsan, Korea, 91p.
|
8 |
Derczynski, L. (2016), Complementarity, F-score, and NLP evaluation, Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), European Language Resources Association (ELRA), pp. 261-266.
|
9 |
Kim, M.J., Bang, H.S., and Lee, J.W. (2017), Accredited use of unmanned aerial vehicle for forecasting pine wood nematode in boundary area: A case study of Sejong metropolitan autonomous city, Korean Society of Forest Science, Vol. 106, No. 1, pp. 100~109. (in Korean with English abstract) https://doi.org/10.14578/jkfs.2017.106.1.100
DOI
|
10 |
Kotsiantis, S., Kanellopoulos, D. and Pintelas, P. (2006). "Handling imbalanced datasets: A review." GESTS International Transactions on Computer Science and Engineering, Vol. 30, No. 1, pp. 25-36.
|
11 |
Jung, Y.J. (2015), Pine wood nematode, The Magazine of The Korean Society of Hazard Mitigation, Vol. 15, pp. 124-128.
|
12 |
Zhang, R.R., You, J., Kim, B.J., Sun, J.N., and Lee, J.H. (2020), Searching the damaged pine trees from wilt disease based on deep learning, Korean Institute of Smart Media, Vol. 9, No. 3, pp. 46-51. (in Korean with English abstract). https://dx.doi.org/10.30693/SMJ.2020.9.3.46
DOI
|
13 |
Olaf, R., Philipp, F., and Thomas B. (2015), U-Net : Convolutional networks for biomedical image segmentation, International Conference on Medical image computing and computer-assisted intervention, 9351, pp. 234~241.
|
14 |
Choi, Y.R., Lee, J.S., and Yun, H.C. (2015), Extraction of forest resources using high density LiDAR data, Journal of the Korean Society of Survey Geodesy Photogrammetry, Vol. 33, No. 2, pp. 73-81. (in Korean with English abstract). https://doi.org/10.7848/ksgpc.2015.33.2.73
DOI
|